Many international video standards are in everyday use around the world, which have different image rates. In an increasingly automated world, intelligent monitoring of ‘live’ system workflows in which media may originate from different video standards, without the intervention of human operators, is a highly desirable capability and a commercial driving force. The problem is that, in order to do this, media identification, system delay and lip-sync monitoring applications need to be capable of accommodating comparisons between different video image rates, across multiple test points at physically separated positions along the broadcast chain, and on a large number of channels. There is currently no industry monitoring solution available to do this.
Video fingerprints (which are also sometimes referred to as ‘signatures’, or ‘hash’ values) can be used to characterize the video content with a low-bandwidth representation. Fingerprints from different test points can usefully be transmitted to a central application for correlation. However, existing systems, including such fingerprinting approaches, deal only with comparisons between video standards with the same image rate, or involve invasive processes, such as the insertion of appropriate test stimuli. These kinds of systems address the problem to a degree, but are only useable in offline, set-up scenarios. Such systems are not suitable for dynamic, non-invasive monitoring.